End-to-end artificial intelligence supports federal mission sets

End-to-end artificial intelligence supports federal mission sets

Advanced computing tools support the AI ​​pipeline

Advanced technologies bring algorithms closer to data. These technologies include high-speed processors, large memory capacities, and AI acceleration tools, all of which can support an efficient AI pipeline.

For example, high-speed processors with built-in tools for quantization, distillation, pruning, and other AI acceleration techniques work with 5G connectivity to deliver more data, faster.

Supported by these tools, it becomes possible to take advantage of Linux containers. A Linux container includes all the services an application needs to run in a single, highly portable package.

“Containerizing” an algorithm, along with all the microservices needed to run it, eliminates the need to send data back to the cloud for processing. Instead, developers can use readily available small form factor computing and storage, along with the 5G communication path, to provide better intelligence at the edge.

End-to-end AI has significant potential benefits for federal agencies. In addition to delivering actionable insights at the point of origin, an end-to-end approach can make data processing less expensive while making it easier to recycle and refine AI as new data emerges.

DIVE DEEPER: Data analytics helps federal agencies act decisively in a crisis.

How end-to-end AI can save lives

For the Department of Defense, an end-to-end strategy can literally save lives by delivering information and resources to troops faster and more efficiently, based on AI-powered insights into field data. battle. The same goes for a whole host of other urgent federal missions.

Agricultural experts, for example, need timely feedback to support precision agriculture, responding to emerging needs with crucial information on water and pesticide use. Health agencies need rapid analyzes to provide the necessary services in the face of public health emergencies.

There’s also a benefit for federal law enforcement, who can mine data feeds from a variety of sources, from social media comments to CCTV cameras to travel records.

With tools like natural language processing and computer vision, investigators are increasingly using AI to connect the dots in cases of human trafficking, child abduction, money laundering. money and other criminal activities. In all of these situations, a streamlined and accelerated AI pipeline can help improve outcomes.

EXAM: The intelligence community is developing new uses for AI.

Take the right path to an end-to-end approach

Federal agencies can start laying the groundwork for an end-to-end AI implementation today.

They can start by having an overall data strategy in place. To do this, they must first look at the data they have and the problems they are trying to solve. The data strategy can help align resources with needs, highlighting where an accelerated approach to AI could help bring that data to life.

When creating your data strategy, it’s important to have an open programming model and integrate open-source and low-code applications. This opens the door to leveraging strong agency domain expertise to chart the journey of data from the edge to the data center and into the cloud.

Second, agencies need to look at their peak resources. Who are the edge users and what are their needs? What devices work at the edge to both generate data and act on AI-supported insights? Leaders can start thinking now about the additional technology resources needed to support an end-to-end approach.

By laying the foundation today, agencies can position themselves to leverage end-to-end AI in support of their most critical data-driven operations. They can bring algorithms closer to data sources, deliver faster results, and improve mission outcomes.

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